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medplot: a web application for dynamic summary and analysis of longitudinal medical data based on R.

Ahlin Č, Stupica D, Strle F, Lusa L - PLoS ONE (2015)

Bottom Line: The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited.The summary tools produce publication-ready tables and graphs.The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer.

View Article: PubMed Central - PubMed

Affiliation: PhD Candidate of Statistics Programme, University of Ljubljana, Ljubljana, Slovenia.

ABSTRACT
In biomedical studies the patients are often evaluated numerous times and a large number of variables are recorded at each time-point. Data entry and manipulation of longitudinal data can be performed using spreadsheet programs, which usually include some data plotting and analysis capabilities and are straightforward to use, but are not designed for the analyses of complex longitudinal data. Specialized statistical software offers more flexibility and capabilities, but first time users with biomedical background often find its use difficult. We developed medplot, an interactive web application that simplifies the exploration and analysis of longitudinal data. The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited. The summary tools produce publication-ready tables and graphs. The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer. This paper describes the application and gives detailed examples describing how to use the application on real data from a clinical study including patients with early Lyme borreliosis.

No MeSH data available.


Related in: MedlinePlus

Data for first two patients of the demo data set.Data for two Erythema migrans patients are displayed. It spans eight rows, as each of them was evaluated on four occasions. Not all recorded variables are displayed.
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pone.0121760.g002: Data for first two patients of the demo data set.Data for two Erythema migrans patients are displayed. It spans eight rows, as each of them was evaluated on four occasions. Not all recorded variables are displayed.

Mentions: For illustration, the rows of the EM data set referring to the first two patients are displayed in Fig 2 (limited to a subset of the variables); the complete data set is also available (https://github.com/crtahlin/medplot/blob/master/inst/extdata/DataEM.txt). The information regarding both patients (identified with PatientID 1 and 2) spans over eight rows, as each of them was evaluated four times; the Date and Measurement variables provide the exact date of evaluation and the evaluation occasion. Some of the additional variables do not change over time (like sex, age, culture), while others were measured at each evaluation occasion and are time-varying (like the intensity of the symptoms).


medplot: a web application for dynamic summary and analysis of longitudinal medical data based on R.

Ahlin Č, Stupica D, Strle F, Lusa L - PLoS ONE (2015)

Data for first two patients of the demo data set.Data for two Erythema migrans patients are displayed. It spans eight rows, as each of them was evaluated on four occasions. Not all recorded variables are displayed.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4383594&req=5

pone.0121760.g002: Data for first two patients of the demo data set.Data for two Erythema migrans patients are displayed. It spans eight rows, as each of them was evaluated on four occasions. Not all recorded variables are displayed.
Mentions: For illustration, the rows of the EM data set referring to the first two patients are displayed in Fig 2 (limited to a subset of the variables); the complete data set is also available (https://github.com/crtahlin/medplot/blob/master/inst/extdata/DataEM.txt). The information regarding both patients (identified with PatientID 1 and 2) spans over eight rows, as each of them was evaluated four times; the Date and Measurement variables provide the exact date of evaluation and the evaluation occasion. Some of the additional variables do not change over time (like sex, age, culture), while others were measured at each evaluation occasion and are time-varying (like the intensity of the symptoms).

Bottom Line: The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited.The summary tools produce publication-ready tables and graphs.The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer.

View Article: PubMed Central - PubMed

Affiliation: PhD Candidate of Statistics Programme, University of Ljubljana, Ljubljana, Slovenia.

ABSTRACT
In biomedical studies the patients are often evaluated numerous times and a large number of variables are recorded at each time-point. Data entry and manipulation of longitudinal data can be performed using spreadsheet programs, which usually include some data plotting and analysis capabilities and are straightforward to use, but are not designed for the analyses of complex longitudinal data. Specialized statistical software offers more flexibility and capabilities, but first time users with biomedical background often find its use difficult. We developed medplot, an interactive web application that simplifies the exploration and analysis of longitudinal data. The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited. The summary tools produce publication-ready tables and graphs. The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user's computer. This paper describes the application and gives detailed examples describing how to use the application on real data from a clinical study including patients with early Lyme borreliosis.

No MeSH data available.


Related in: MedlinePlus